1. Statement of the Technical Field
The invention is directed to biometric systems. In particular, the invention is directed to fingerprint inpainting including automatic identification of fingerprint inpainting target areas.
2. Description of the Related Art
Biometric systems are used to identify individuals based on their unique traits. Biometrics are useful in many applications, including security and forensics. Some physical biometric markers include facial features, fingerprints, hand geometry, and iris and retinal scans. A biometric system can authenticate a user or determine the identity of sampled data by querying a database.
There are many advantages to using biometric systems. Most biometric markers are easily collectable, present in most individuals, unique between individuals, and permanent throughout the lifespan of an individual. However, these factors are not guaranteed. For example, surgical alterations may be used to change a biometric feature such that it does not match one previously collected from the same individual. Furthermore, different biometric features can change over time.
A common type of biometric identification is fingerprinting. A fingerprint is an impression of the raised friction ridges on the epidermis. In general, fingerprints have lasting permanence and are unique to an individual, making them a robust means for identification. Additionally, fingerprints are easily collectable, as they may be collected from many types of surfaces. Fingerprints are more intrusive than some less accurate biometric identification methods, such as facial recognition or voice print identification methods. Still, they are less intrusive than other accurate biometric identification methods, such as iris scans and DNA. As a result, fingerprints are currently the most common type of biometric identification and are likely to remain so for the foreseeable future.
The use of fingerprints as a form of biometric identification began with manual methods for collecting fingerprints and evaluating matches. Identification was performed at one time by manually comparing a collected fingerprint to fingerprints on a card collected using an “ink technique” (i.e., pressing and rolling an individual subject's inked finger). Such methods have now been automated by the use of automated identification systems to compare fingerprint images. The term “fingerprint image” as used herein refers to a digital image of a fingerprint. The “ink technique” is still in use today; however these cards are now scanned to create fingerprint images for use in automated identification systems. In addition to the “ink technique”, fingerprint images can also be generated via the use of solid-state fingerprint readers. Solid-state fingerprint sensors generally work based on capacitance, thermal, electric field, laser, radio frequency, and/or other principles. Such fingerprint sensors typically generate 2-dimensional fingerprint images, although some fingerprint sensors generate 3-dimensional fingerprint images.
Even though fingerprints are unique across individuals, they generally include several types or levels of common or “key” features. Automated identification systems utilize such key features during fingerprint recognition processes. That is, these systems compare the locations, number, and types of key features in an acquired fingerprint image to determine the identity of the individual associated with the acquired fingerprint. Level 1 features of fingerprints include loops, whorls and arches formed by the ridges. These features describe the overall shape followed by the ridges. Level 2 features of fingerprints, or minutiae, are irregularities or discontinuities in the ridges. These include ridge terminations, bifurcations, and dots. Level 3 features of fingerprints include ridge pores, ridge shape, as well as scarring, warts, creases and other deformations.